Data Sciences Software Engineer bei None

SUMMARY

The Data Sciences Software Engineer is responsible for designing, building, and maintaining modern data infrastructure and analytical solutions to support business intelligence, precision agriculture, predictive modeling, and decision support systems. This role is critical in enabling data-driven insights by developing a scalable Data Lakehouse, implementing data integration pipelines, and leveraging advanced analytics and machine learning techniques to optimize agricultural operations and business performance.

ESSENTIAL DUTIES AND RESPONSIBILITIES 

(Includes the following and other duties may be assigned)

Key Responsibilities:

1. Data Lakehouse Architecture & Development

• Design, develop, and implement a scalable Data Lakehouse environment to integrate structured, semi-structured, and unstructured data sources, including IoT, satellite imagery, weather data, and field telemetry.
• Ensure the Data Lakehouse supports efficient data storage, retrieval, governance, and security.

2. Data Integration & ETL/ELT Pipelines

• Implement robust ETL/ELT processes to collect, transform, and load data from diverse internal and external sources into the Lakehouse environment.
• Integrate data from agricultural equipment, ERP systems, cloud platforms, and third-party APIs.
• Select and configure appropriate ETL tools and platforms (e.g., Apache Airflow, Talend, dbt, AWS Glue) to support repeatable, scalable workflows.

3. Data Analytics & Platform Tools

• Deploy and manage data analytics and visualization platforms (e.g., Power BI, Tableau, Looker, KNIME) and support cross-functional teams in generating actionable insights.
• Work closely with key technology stakeholders to enable advanced analytics, predictive modeling, and machine learning workflows.
• Optimize query performance and resource usage for large-scale datasets.

4. Data Governance & Security

• Define and implement data governance, access control, and data quality standards to ensure compliance and accuracy across systems.
• Maintain robust security protocols and regulatory compliance (e.g., GDPR, data privacy standards).

5. Collaboration & Cross-Functional Support

• Collaborate with agronomists, operations, finance, and product teams to understand data needs and translate them into technical solutions.
• Support agricultural technology initiatives, including IoT sensor data ingestion, satellite imagery analysis, and AI-driven decision support.

6. Emerging Technology & Best Practices

• Continuously evaluate new technologies, frameworks, and industry trends in cloud computing, big data, and AI to enhance organizational capabilities.
• Work with and support DevOps practices, including CI/CD pipelines and infrastructure & platform as code.

7. Company specific Principles and Practices

• Adherence to safety policies.
• Promoting and adhering to the company Core Values of honesty, integrity & teamwork.
  • Promptly and regularly report to work and work overtime hours as needed.
  • Securing facilities and equipment when closing.
  • Works with other cooperative staff at other locations to ensure cooperative goals are met.
  • Present a clean and professional appearance.
  • Employee is required to perform all other duties as directed.

SUPERVISORY RESPONSIBILITIES 

This position has no supervisory responsibilities.

QUALIFICATIONS, SKILLS, EDUCATION & EXPERIENCE 

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or related field.
• 3+ years of experience in data engineering or data platform development.
• Proficiency with ANSI SQL and NoSQL databases, Python/ R / C++ and data modeling techniques.
• Experience with cloud platforms (AWS, Azure, GCP) and data lakehouse technologies (Delta Lake, Snowflake, Databricks etc.).
• Knowledge of ETL tools and orchestration frameworks and proficiency in API integration.
• Understanding of data governance, security, and compliance.
• Experience with agriculture technology, geospatial data, or IoT telemetry.
• Familiarity with machine learning workflows, MLOps, and AI-based decision systems.
• Strong understanding of data visualization best practices.
• Experience deploying solutions in containerized environments (Docker, Kubernetes).
• Experience integrating AI agents and / or MCPs across various LLM models.

LANGUAGE SKILLS 

Ability to read and interpret documents such as safety rules, operating and maintenance instructions, and procedure manuals.   Ability to write routine reports and correspondence.  Ability to speak effectively before groups of customers or employees of organization.  

MINIMUM MATHEMATICAL SKILLS 

The role requires a solid foundation in applied mathematics, including proficiency in linear algebra, probability, and statistics to support data modeling, algorithm development, and predictive analytics. Candidates should be comfortable with concepts such as regression analysis, hypothesis testing, optimization, and time-series analysis, with the ability to apply these methods to real-world data integration and agricultural analytics challenges. 

ADVANCED MATHEMATICAL SKILLS (A PLUS however, not required)

While deep theoretical research is not required, the ability to translate mathematical methods into practical software solutions and collaborate effectively with data scientists on advanced models is essential.  Fourier analysis, and spatial statistics will be advantageous for precision agriculture applications involving geospatial data, satellite imagery, and IoT sensor streams. Candidates who can bridge advanced mathematical concepts with practical data engineering and software implementations will be well-positioned to lead innovation in predictive modeling and decision support systems.

CERTIFICATES, LICENSES, AND REGISTRATION

This position does not require certificates however, Databricks or Snowflake certification is a plus.

REASONING & CRITICAL THINKING ABILITY

The ability to apply common sense understanding to carry out instructions furnished in written, oral, or diagram form.  Able to deal with problems with several concrete variables in standard situations.   Must be able to think quickly and perform a mental assessment of workplace hazards, take appropriate precautions, and choose appropriate PPE as dictated by need, regulation and labeling. 

PHYSICAL DEMANDS

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.   Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.  

While performing the duties of this job, the employee is frequently required to use hands to finger, handle, or feel; reach with hands and arms, talk or hear, taste or smell; stand; walk; sit and climb or balance.  The employee is required to regularly stand or sit for long periods of time.  The employee is occasionally required to stoop, kneel, crouch, or crawl.  The employee must occasionally lift and/or move up to 50 pounds.  Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus

WORK ENVIRONMENT  

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Employee must understand and implement all related safety policies, procedures and programs for prevention and protection while performing job duties in various work environments.

The noise level in the work environment is usually moderate.